Overview

Dataset statistics

Number of variables18
Number of observations14396
Missing cells5483
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 MiB
Average record size in memory144.0 B

Variable types

Numeric14
Categorical4

Alerts

Artist Name has a high cardinality: 7913 distinct valuesHigh cardinality
Track Name has a high cardinality: 12455 distinct valuesHigh cardinality
energy is highly overall correlated with loudness and 1 other fieldsHigh correlation
loudness is highly overall correlated with energy and 1 other fieldsHigh correlation
acousticness is highly overall correlated with energy and 1 other fieldsHigh correlation
time_signature is highly imbalanced (74.8%)Imbalance
Popularity has 333 (2.3%) missing valuesMissing
key has 1609 (11.2%) missing valuesMissing
instrumentalness has 3541 (24.6%) missing valuesMissing
Id is uniformly distributedUniform
Track Name is uniformly distributedUniform
Id has unique valuesUnique
Class has 500 (3.5%) zerosZeros

Reproduction

Analysis started2023-08-29 08:53:15.557684
Analysis finished2023-08-29 08:54:06.796203
Duration51.24 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

Id
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct14396
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7198.5
Minimum1
Maximum14396
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:07.050044image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile720.75
Q13599.75
median7198.5
Q310797.25
95-th percentile13676.25
Maximum14396
Range14395
Interquartile range (IQR)7197.5

Descriptive statistics

Standard deviation4155.9116
Coefficient of variation (CV)0.57733022
Kurtosis-1.2
Mean7198.5
Median Absolute Deviation (MAD)3599
Skewness0
Sum1.0362961 × 108
Variance17271601
MonotonicityStrictly increasing
2023-08-29T11:54:07.336865image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
9673 1
 
< 0.1%
9591 1
 
< 0.1%
9592 1
 
< 0.1%
9593 1
 
< 0.1%
9594 1
 
< 0.1%
9595 1
 
< 0.1%
9596 1
 
< 0.1%
9597 1
 
< 0.1%
9598 1
 
< 0.1%
Other values (14386) 14386
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
14396 1
< 0.1%
14395 1
< 0.1%
14394 1
< 0.1%
14393 1
< 0.1%
14392 1
< 0.1%
14391 1
< 0.1%
14390 1
< 0.1%
14389 1
< 0.1%
14388 1
< 0.1%
14387 1
< 0.1%

Artist Name
Categorical

Distinct7913
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size112.6 KiB
Backstreet Boys
 
58
Westlife
 
53
Britney Spears
 
47
Omer Adam
 
39
Eyal Golan
 
38
Other values (7908)
14161 

Length

Max length153
Median length94
Mean length12.250278
Min length1

Characters and Unicode

Total characters176355
Distinct characters169
Distinct categories15 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5289 ?
Unique (%)36.7%

Sample

1st rowMarina Maximilian
2nd rowThe Black Keys
3rd rowRoyal & the Serpent
4th rowDetroit Blues Band
5th rowCoast Contra

Common Values

ValueCountFrequency (%)
Backstreet Boys 58
 
0.4%
Westlife 53
 
0.4%
Britney Spears 47
 
0.3%
Omer Adam 39
 
0.3%
Eyal Golan 38
 
0.3%
Shlomo Artzi 32
 
0.2%
Dudu Aharon 29
 
0.2%
Arik Einstein 29
 
0.2%
Hadag Nahash 29
 
0.2%
Moshe Peretz 27
 
0.2%
Other values (7903) 14015
97.4%

Length

2023-08-29T11:54:07.699641image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 1410
 
4.8%
239
 
0.8%
of 192
 
0.7%
john 108
 
0.4%
boys 104
 
0.4%
black 101
 
0.3%
band 99
 
0.3%
and 99
 
0.3%
king 72
 
0.2%
james 68
 
0.2%
Other values (9512) 26987
91.5%

Most occurring characters

ValueCountFrequency (%)
e 15848
 
9.0%
15083
 
8.6%
a 14054
 
8.0%
i 9883
 
5.6%
n 9728
 
5.5%
r 9658
 
5.5%
o 9310
 
5.3%
s 7321
 
4.2%
l 7256
 
4.1%
t 6883
 
3.9%
Other values (159) 71331
40.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 125331
71.1%
Uppercase Letter 32545
 
18.5%
Space Separator 15083
 
8.6%
Other Punctuation 1764
 
1.0%
Decimal Number 471
 
0.3%
Dash Punctuation 379
 
0.2%
Other Symbol 309
 
0.2%
Math Symbol 296
 
0.2%
Open Punctuation 61
 
< 0.1%
Close Punctuation 38
 
< 0.1%
Other values (5) 78
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15848
12.6%
a 14054
11.2%
i 9883
 
7.9%
n 9728
 
7.8%
r 9658
 
7.7%
o 9310
 
7.4%
s 7321
 
5.8%
l 7256
 
5.8%
t 6883
 
5.5%
h 5767
 
4.6%
Other values (52) 29623
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 2842
 
8.7%
T 2758
 
8.5%
B 2547
 
7.8%
M 2231
 
6.9%
A 2169
 
6.7%
C 1851
 
5.7%
D 1635
 
5.0%
R 1578
 
4.8%
L 1501
 
4.6%
P 1333
 
4.1%
Other values (31) 12100
37.2%
Math Symbol
ValueCountFrequency (%)
167
56.4%
23
 
7.8%
19
 
6.4%
13
 
4.4%
± 11
 
3.7%
11
 
3.7%
+ 10
 
3.4%
10
 
3.4%
10
 
3.4%
8
 
2.7%
Other values (6) 14
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 713
40.4%
. 564
32.0%
& 221
 
12.5%
' 118
 
6.7%
" 42
 
2.4%
/ 35
 
2.0%
! 19
 
1.1%
13
 
0.7%
: 10
 
0.6%
§ 9
 
0.5%
Other values (5) 20
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 76
16.1%
3 66
14.0%
2 61
13.0%
9 54
11.5%
0 54
11.5%
4 39
8.3%
7 37
7.9%
5 36
7.6%
8 25
 
5.3%
6 23
 
4.9%
Other Symbol
ValueCountFrequency (%)
208
67.3%
© 50
 
16.2%
° 22
 
7.1%
® 16
 
5.2%
13
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 31
50.8%
17
27.9%
9
 
14.8%
[ 4
 
6.6%
Currency Symbol
ValueCountFrequency (%)
$ 18
54.5%
¢ 7
 
21.2%
£ 4
 
12.1%
¥ 4
 
12.1%
Dash Punctuation
ValueCountFrequency (%)
- 160
42.2%
151
39.8%
68
17.9%
Close Punctuation
ValueCountFrequency (%)
) 34
89.5%
] 4
 
10.5%
Other Letter
ValueCountFrequency (%)
º 28
77.8%
ª 8
 
22.2%
Modifier Symbol
ValueCountFrequency (%)
´ 3
60.0%
¨ 2
40.0%
Space Separator
ValueCountFrequency (%)
15083
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 157875
89.5%
Common 18456
 
10.5%
Greek 24
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15848
 
10.0%
a 14054
 
8.9%
i 9883
 
6.3%
n 9728
 
6.2%
r 9658
 
6.1%
o 9310
 
5.9%
s 7321
 
4.6%
l 7256
 
4.6%
t 6883
 
4.4%
h 5767
 
3.7%
Other values (92) 62167
39.4%
Common
ValueCountFrequency (%)
15083
81.7%
, 713
 
3.9%
. 564
 
3.1%
& 221
 
1.2%
208
 
1.1%
167
 
0.9%
- 160
 
0.9%
151
 
0.8%
' 118
 
0.6%
1 76
 
0.4%
Other values (55) 995
 
5.4%
Greek
ValueCountFrequency (%)
Ω 17
70.8%
π 7
29.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 174913
99.2%
None 692
 
0.4%
Math Operators 267
 
0.2%
Punctuation 262
 
0.1%
Geometric Shapes 208
 
0.1%
Letterlike Symbols 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 15848
 
9.1%
15083
 
8.6%
a 14054
 
8.0%
i 9883
 
5.7%
n 9728
 
5.6%
r 9658
 
5.5%
o 9310
 
5.3%
s 7321
 
4.2%
l 7256
 
4.1%
t 6883
 
3.9%
Other values (75) 69889
40.0%
Geometric Shapes
ValueCountFrequency (%)
208
100.0%
Math Operators
ValueCountFrequency (%)
167
62.5%
23
 
8.6%
19
 
7.1%
13
 
4.9%
11
 
4.1%
10
 
3.7%
10
 
3.7%
8
 
3.0%
5
 
1.9%
1
 
0.4%
Punctuation
ValueCountFrequency (%)
151
57.6%
68
26.0%
17
 
6.5%
13
 
5.0%
9
 
3.4%
3
 
1.1%
1
 
0.4%
None
ValueCountFrequency (%)
© 50
 
7.2%
é 36
 
5.2%
Ä 32
 
4.6%
ô 30
 
4.3%
º 28
 
4.0%
ï 27
 
3.9%
ë 25
 
3.6%
É 23
 
3.3%
° 22
 
3.2%
ò 21
 
3.0%
Other values (55) 398
57.5%
Letterlike Symbols
ValueCountFrequency (%)
13
100.0%

Track Name
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct12455
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size112.6 KiB
Fire
 
8
Ghost
 
7
Runaway
 
7
Forever
 
6
Dreams
 
6
Other values (12450)
14362 

Length

Max length114
Median length89
Mean length16.944012
Min length1

Characters and Unicode

Total characters243926
Distinct characters183
Distinct categories17 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10929 ?
Unique (%)75.9%

Sample

1st rowNot Afraid
2nd rowHowlin' for You
3rd rowphuck u
4th rowMissing You
5th rowMy Lady

Common Values

ValueCountFrequency (%)
Fire 8
 
0.1%
Ghost 7
 
< 0.1%
Runaway 7
 
< 0.1%
Forever 6
 
< 0.1%
Dreams 6
 
< 0.1%
Control 6
 
< 0.1%
Hurricane 6
 
< 0.1%
Change 5
 
< 0.1%
All My Friends 5
 
< 0.1%
Patience 5
 
< 0.1%
Other values (12445) 14335
99.6%

Length

2023-08-29T11:54:08.070413image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1646
 
3.7%
the 1563
 
3.5%
you 643
 
1.4%
of 532
 
1.2%
feat 520
 
1.2%
a 497
 
1.1%
i 492
 
1.1%
in 489
 
1.1%
to 441
 
1.0%
me 439
 
1.0%
Other values (10764) 37484
83.8%

Most occurring characters

ValueCountFrequency (%)
30351
 
12.4%
e 21100
 
8.7%
a 13878
 
5.7%
o 13176
 
5.4%
i 11407
 
4.7%
n 11239
 
4.6%
t 10719
 
4.4%
r 10130
 
4.2%
7889
 
3.2%
s 7679
 
3.1%
Other values (173) 106358
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 154038
63.1%
Uppercase Letter 39407
 
16.2%
Space Separator 30351
 
12.4%
Other Symbol 9285
 
3.8%
Other Punctuation 3726
 
1.5%
Decimal Number 2368
 
1.0%
Dash Punctuation 1774
 
0.7%
Open Punctuation 1204
 
0.5%
Close Punctuation 1106
 
0.5%
Math Symbol 320
 
0.1%
Other values (7) 347
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 21100
13.7%
a 13878
 
9.0%
o 13176
 
8.6%
i 11407
 
7.4%
n 11239
 
7.3%
t 10719
 
7.0%
r 10130
 
6.6%
s 7679
 
5.0%
l 7221
 
4.7%
h 6123
 
4.0%
Other values (48) 41366
26.9%
Uppercase Letter
ValueCountFrequency (%)
S 3390
 
8.6%
T 3244
 
8.2%
M 2766
 
7.0%
B 2533
 
6.4%
A 2363
 
6.0%
L 2213
 
5.6%
R 1993
 
5.1%
I 1927
 
4.9%
D 1904
 
4.8%
W 1883
 
4.8%
Other values (37) 15191
38.5%
Other Punctuation
ValueCountFrequency (%)
. 997
26.8%
' 923
24.8%
, 479
12.9%
266
 
7.1%
& 262
 
7.0%
§ 155
 
4.2%
/ 153
 
4.1%
! 99
 
2.7%
? 96
 
2.6%
92
 
2.5%
Other values (10) 204
 
5.5%
Math Symbol
ValueCountFrequency (%)
133
41.6%
43
 
13.4%
26
 
8.1%
23
 
7.2%
20
 
6.2%
± 20
 
6.2%
12
 
3.8%
10
 
3.1%
9
 
2.8%
8
 
2.5%
Other values (6) 16
 
5.0%
Decimal Number
ValueCountFrequency (%)
0 577
24.4%
2 477
20.1%
1 443
18.7%
9 250
10.6%
6 121
 
5.1%
3 114
 
4.8%
5 111
 
4.7%
4 100
 
4.2%
8 92
 
3.9%
7 83
 
3.5%
Other Symbol
ValueCountFrequency (%)
7889
85.0%
438
 
4.7%
® 429
 
4.6%
© 368
 
4.0%
° 161
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 1086
90.2%
68
 
5.6%
29
 
2.4%
[ 20
 
1.7%
{ 1
 
0.1%
Currency Symbol
ValueCountFrequency (%)
¢ 226
78.7%
£ 36
 
12.5%
$ 18
 
6.3%
¥ 7
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1408
79.4%
276
 
15.6%
90
 
5.1%
Close Punctuation
ValueCountFrequency (%)
) 1085
98.1%
] 20
 
1.8%
} 1
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
¨ 5
50.0%
´ 3
30.0%
^ 2
 
20.0%
Other Letter
ValueCountFrequency (%)
º 22
57.9%
ª 16
42.1%
Final Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Initial Punctuation
ValueCountFrequency (%)
1
50.0%
« 1
50.0%
Space Separator
ValueCountFrequency (%)
30351
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Nonspacing Mark
ValueCountFrequency (%)
́ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 193412
79.3%
Common 50473
 
20.7%
Greek 40
 
< 0.1%
Inherited 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 21100
 
10.9%
a 13878
 
7.2%
o 13176
 
6.8%
i 11407
 
5.9%
n 11239
 
5.8%
t 10719
 
5.5%
r 10130
 
5.2%
s 7679
 
4.0%
l 7221
 
3.7%
h 6123
 
3.2%
Other values (94) 80740
41.7%
Common
ValueCountFrequency (%)
30351
60.1%
7889
 
15.6%
- 1408
 
2.8%
( 1086
 
2.2%
) 1085
 
2.1%
. 997
 
2.0%
' 923
 
1.8%
0 577
 
1.1%
, 479
 
0.9%
2 477
 
0.9%
Other values (66) 5201
 
10.3%
Greek
ValueCountFrequency (%)
Ω 28
70.0%
π 12
30.0%
Inherited
ValueCountFrequency (%)
́ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 226617
92.9%
None 7930
 
3.3%
Geometric Shapes 7889
 
3.2%
Punctuation 762
 
0.3%
Letterlike Symbols 438
 
0.2%
Math Operators 289
 
0.1%
Diacriticals 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30351
 
13.4%
e 21100
 
9.3%
a 13878
 
6.1%
o 13176
 
5.8%
i 11407
 
5.0%
n 11239
 
5.0%
t 10719
 
4.7%
r 10130
 
4.5%
s 7679
 
3.4%
l 7221
 
3.2%
Other values (82) 89717
39.6%
Geometric Shapes
ValueCountFrequency (%)
7889
100.0%
None
ValueCountFrequency (%)
ô 1041
13.1%
ï 754
 
9.5%
ú 634
 
8.0%
î 633
 
8.0%
ê 538
 
6.8%
® 429
 
5.4%
û 412
 
5.2%
ë 370
 
4.7%
© 368
 
4.6%
ù 258
 
3.3%
Other values (58) 2493
31.4%
Letterlike Symbols
ValueCountFrequency (%)
438
100.0%
Punctuation
ValueCountFrequency (%)
276
36.2%
266
34.9%
90
 
11.8%
68
 
8.9%
29
 
3.8%
23
 
3.0%
4
 
0.5%
4
 
0.5%
1
 
0.1%
1
 
0.1%
Math Operators
ValueCountFrequency (%)
133
46.0%
43
 
14.9%
26
 
9.0%
23
 
8.0%
20
 
6.9%
12
 
4.2%
10
 
3.5%
9
 
3.1%
8
 
2.8%
5
 
1.7%
Diacriticals
ValueCountFrequency (%)
́ 1
100.0%

Popularity
Real number (ℝ)

Distinct100
Distinct (%)0.7%
Missing333
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean44.525208
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:08.407202image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16
Q133
median44
Q356
95-th percentile75
Maximum100
Range99
Interquartile range (IQR)23

Descriptive statistics

Standard deviation17.41894
Coefficient of variation (CV)0.39121525
Kurtosis-0.19790812
Mean44.525208
Median Absolute Deviation (MAD)12
Skewness0.075790464
Sum626158
Variance303.41949
MonotonicityNot monotonic
2023-08-29T11:54:08.715010image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 371
 
2.6%
41 357
 
2.5%
34 348
 
2.4%
43 343
 
2.4%
44 333
 
2.3%
37 328
 
2.3%
46 325
 
2.3%
40 323
 
2.2%
38 313
 
2.2%
32 311
 
2.2%
Other values (90) 10711
74.4%
(Missing) 333
 
2.3%
ValueCountFrequency (%)
1 58
0.4%
2 47
0.3%
3 39
0.3%
4 30
0.2%
5 31
0.2%
6 27
0.2%
7 28
0.2%
8 37
0.3%
9 43
0.3%
10 49
0.3%
ValueCountFrequency (%)
100 2
 
< 0.1%
99 1
 
< 0.1%
98 1
 
< 0.1%
97 3
 
< 0.1%
96 2
 
< 0.1%
95 8
0.1%
94 4
< 0.1%
93 4
< 0.1%
92 4
< 0.1%
91 3
 
< 0.1%

danceability
Real number (ℝ)

Distinct887
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.54310536
Minimum0.0596
Maximum0.989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:09.021819image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0.0596
5-th percentile0.263
Q10.432
median0.545
Q30.658
95-th percentile0.817
Maximum0.989
Range0.9294
Interquartile range (IQR)0.226

Descriptive statistics

Standard deviation0.16551701
Coefficient of variation (CV)0.30476041
Kurtosis-0.27990009
Mean0.54310536
Median Absolute Deviation (MAD)0.113
Skewness-0.075651149
Sum7818.5447
Variance0.027395882
MonotonicityNot monotonic
2023-08-29T11:54:09.309641image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.552 54
 
0.4%
0.532 48
 
0.3%
0.527 47
 
0.3%
0.529 47
 
0.3%
0.601 47
 
0.3%
0.566 46
 
0.3%
0.546 45
 
0.3%
0.508 45
 
0.3%
0.567 45
 
0.3%
0.5 44
 
0.3%
Other values (877) 13928
96.7%
ValueCountFrequency (%)
0.0596 1
< 0.1%
0.0599 1
< 0.1%
0.0644 1
< 0.1%
0.065 1
< 0.1%
0.069 1
< 0.1%
0.0726 1
< 0.1%
0.075 1
< 0.1%
0.0755 1
< 0.1%
0.0756 1
< 0.1%
0.0764 1
< 0.1%
ValueCountFrequency (%)
0.989 1
 
< 0.1%
0.982 2
< 0.1%
0.98 3
< 0.1%
0.979 1
 
< 0.1%
0.974 1
 
< 0.1%
0.973 1
 
< 0.1%
0.968 1
 
< 0.1%
0.967 2
< 0.1%
0.965 2
< 0.1%
0.964 1
 
< 0.1%

energy
Real number (ℝ)

Distinct1156
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66242165
Minimum0.00121
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:09.613451image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0.00121
5-th percentile0.199
Q10.508
median0.699
Q30.861
95-th percentile0.967
Maximum1
Range0.99879
Interquartile range (IQR)0.353

Descriptive statistics

Standard deviation0.23596748
Coefficient of variation (CV)0.35621946
Kurtosis-0.32864007
Mean0.66242165
Median Absolute Deviation (MAD)0.173
Skewness-0.65669815
Sum9536.222
Variance0.055680653
MonotonicityNot monotonic
2023-08-29T11:54:09.905272image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.948 43
 
0.3%
0.914 43
 
0.3%
0.971 42
 
0.3%
0.931 42
 
0.3%
0.947 41
 
0.3%
0.932 41
 
0.3%
0.964 41
 
0.3%
0.872 41
 
0.3%
0.913 39
 
0.3%
0.696 37
 
0.3%
Other values (1146) 13986
97.2%
ValueCountFrequency (%)
0.00121 1
< 0.1%
0.00124 1
< 0.1%
0.0017 1
< 0.1%
0.00395 1
< 0.1%
0.00554 1
< 0.1%
0.00573 1
< 0.1%
0.00626 1
< 0.1%
0.00711 1
< 0.1%
0.00717 1
< 0.1%
0.0072 1
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0.999 1
 
< 0.1%
0.998 8
 
0.1%
0.997 9
 
0.1%
0.996 11
0.1%
0.995 16
0.1%
0.994 18
0.1%
0.993 25
0.2%
0.992 22
0.2%
0.991 16
0.1%

key
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing1609
Missing (%)11.2%
Infinite0
Infinite (%)0.0%
Mean5.9537812
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:10.180102image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile11
Maximum11
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.2000128
Coefficient of variation (CV)0.53747571
Kurtosis-1.2183793
Mean5.9537812
Median Absolute Deviation (MAD)3
Skewness-0.054521092
Sum76131
Variance10.240082
MonotonicityNot monotonic
2023-08-29T11:54:10.382977image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
7 1650
11.5%
9 1590
11.0%
2 1582
11.0%
1 1351
9.4%
4 1252
8.7%
11 1176
8.2%
5 1115
7.7%
6 963
6.7%
8 872
6.1%
10 825
5.7%
(Missing) 1609
11.2%
ValueCountFrequency (%)
1 1351
9.4%
2 1582
11.0%
3 411
 
2.9%
4 1252
8.7%
5 1115
7.7%
6 963
6.7%
7 1650
11.5%
8 872
6.1%
9 1590
11.0%
10 825
5.7%
ValueCountFrequency (%)
11 1176
8.2%
10 825
5.7%
9 1590
11.0%
8 872
6.1%
7 1650
11.5%
6 963
6.7%
5 1115
7.7%
4 1252
8.7%
3 411
 
2.9%
2 1582
11.0%

loudness
Real number (ℝ)

Distinct8051
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-7.9008522
Minimum-39.952
Maximum1.342
Zeros0
Zeros (%)0.0%
Negative14389
Negative (%)> 99.9%
Memory size112.6 KiB
2023-08-29T11:54:10.629823image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum-39.952
5-th percentile-15.58825
Q1-9.538
median-7.0135
Q3-5.162
95-th percentile-3.28175
Maximum1.342
Range41.294
Interquartile range (IQR)4.376

Descriptive statistics

Standard deviation4.0573622
Coefficient of variation (CV)-0.51353476
Kurtosis4.9797437
Mean-7.9008522
Median Absolute Deviation (MAD)2.1005
Skewness-1.7480727
Sum-113740.67
Variance16.462188
MonotonicityNot monotonic
2023-08-29T11:54:10.924639image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.497 12
 
0.1%
-4.818 10
 
0.1%
-4.261 10
 
0.1%
-6.481 8
 
0.1%
-4.633 8
 
0.1%
-4.448 8
 
0.1%
-6.938 8
 
0.1%
-4.975 8
 
0.1%
-4.671 8
 
0.1%
-5.218 8
 
0.1%
Other values (8041) 14308
99.4%
ValueCountFrequency (%)
-39.952 1
< 0.1%
-36.214 1
< 0.1%
-35.154 1
< 0.1%
-34.825 1
< 0.1%
-34.378 1
< 0.1%
-33.395 1
< 0.1%
-33.082 1
< 0.1%
-32.796 1
< 0.1%
-32.22 1
< 0.1%
-31.858 1
< 0.1%
ValueCountFrequency (%)
1.342 2
< 0.1%
0.943 1
< 0.1%
0.878 1
< 0.1%
0.732 1
< 0.1%
0.119 1
< 0.1%
0.101 1
< 0.1%
-0.467 1
< 0.1%
-0.489 1
< 0.1%
-0.645 1
< 0.1%
-0.734 1
< 0.1%

mode
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.6 KiB
1
9217 
0
5179 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters14396
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 9217
64.0%
0 5179
36.0%

Length

2023-08-29T11:54:11.201470image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T11:54:12.350754image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
1 9217
64.0%
0 5179
36.0%

Most occurring characters

ValueCountFrequency (%)
1 9217
64.0%
0 5179
36.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14396
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9217
64.0%
0 5179
36.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9217
64.0%
0 5179
36.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9217
64.0%
0 5179
36.0%

speechiness
Real number (ℝ)

Distinct1177
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.080180647
Minimum0.0225
Maximum0.955
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:12.608595image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0.0225
5-th percentile0.0278
Q10.0348
median0.0471
Q30.0831
95-th percentile0.278
Maximum0.955
Range0.9325
Interquartile range (IQR)0.0483

Descriptive statistics

Standard deviation0.085156593
Coefficient of variation (CV)1.0620592
Kurtosis12.870291
Mean0.080180647
Median Absolute Deviation (MAD)0.0155
Skewness3.1133954
Sum1154.2806
Variance0.0072516454
MonotonicityNot monotonic
2023-08-29T11:54:12.911408image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0315 63
 
0.4%
0.0317 61
 
0.4%
0.031 54
 
0.4%
0.0339 54
 
0.4%
0.0302 53
 
0.4%
0.0323 53
 
0.4%
0.0346 51
 
0.4%
0.0344 50
 
0.3%
0.0362 50
 
0.3%
0.0319 50
 
0.3%
Other values (1167) 13857
96.3%
ValueCountFrequency (%)
0.0225 2
< 0.1%
0.0227 1
 
< 0.1%
0.023 2
< 0.1%
0.0231 1
 
< 0.1%
0.0232 4
< 0.1%
0.0233 4
< 0.1%
0.0234 3
< 0.1%
0.0235 2
< 0.1%
0.0236 3
< 0.1%
0.0237 1
 
< 0.1%
ValueCountFrequency (%)
0.955 1
< 0.1%
0.937 1
< 0.1%
0.935 1
< 0.1%
0.92 1
< 0.1%
0.891 1
< 0.1%
0.872 1
< 0.1%
0.862 1
< 0.1%
0.851 1
< 0.1%
0.84 1
< 0.1%
0.73 1
< 0.1%

acousticness
Real number (ℝ)

Distinct3725
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24674571
Minimum0
Maximum0.996
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:13.248200image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.265 × 10-5
Q10.00428
median0.08145
Q30.43225
95-th percentile0.917
Maximum0.996
Range0.996
Interquartile range (IQR)0.42797

Descriptive statistics

Standard deviation0.31092196
Coefficient of variation (CV)1.2600906
Kurtosis-0.17902357
Mean0.24674571
Median Absolute Deviation (MAD)0.081284
Skewness1.1089328
Sum3552.1512
Variance0.096672464
MonotonicityNot monotonic
2023-08-29T11:54:13.553010image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.102 27
 
0.2%
0.13 24
 
0.2%
0.128 24
 
0.2%
0.135 23
 
0.2%
0.124 22
 
0.2%
0.136 21
 
0.1%
0.117 20
 
0.1%
0.103 20
 
0.1%
0.207 20
 
0.1%
0.993 19
 
0.1%
Other values (3715) 14176
98.5%
ValueCountFrequency (%)
0 3
< 0.1%
1.02 × 10-61
 
< 0.1%
1.06 × 10-61
 
< 0.1%
1.11 × 10-61
 
< 0.1%
1.19 × 10-61
 
< 0.1%
1.23 × 10-61
 
< 0.1%
1.26 × 10-61
 
< 0.1%
1.27 × 10-61
 
< 0.1%
1.31 × 10-62
< 0.1%
1.33 × 10-61
 
< 0.1%
ValueCountFrequency (%)
0.996 4
 
< 0.1%
0.995 7
 
< 0.1%
0.994 18
0.1%
0.993 19
0.1%
0.992 17
0.1%
0.991 11
0.1%
0.99 13
0.1%
0.989 18
0.1%
0.988 8
0.1%
0.987 13
0.1%

instrumentalness
Real number (ℝ)

Distinct3945
Distinct (%)36.3%
Missing3541
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean0.17812872
Minimum1 × 10-6
Maximum0.996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:13.853822image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum1 × 10-6
5-th percentile2.7 × 10-6
Q18.755 × 10-5
median0.00392
Q30.201
95-th percentile0.888
Maximum0.996
Range0.995999
Interquartile range (IQR)0.20091245

Descriptive statistics

Standard deviation0.30426567
Coefficient of variation (CV)1.7081225
Kurtosis0.7021881
Mean0.17812872
Median Absolute Deviation (MAD)0.00391765
Skewness1.525166
Sum1933.5872
Variance0.092577596
MonotonicityNot monotonic
2023-08-29T11:54:14.173624image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.000109 18
 
0.1%
0.929 17
 
0.1%
0.899 16
 
0.1%
0.914 16
 
0.1%
0.927 15
 
0.1%
0.112 14
 
0.1%
0.0102 14
 
0.1%
0.918 14
 
0.1%
0.892 14
 
0.1%
0.925 13
 
0.1%
Other values (3935) 10704
74.4%
(Missing) 3541
 
24.6%
ValueCountFrequency (%)
1 × 10-62
 
< 0.1%
1.01 × 10-66
< 0.1%
1.02 × 10-67
< 0.1%
1.03 × 10-66
< 0.1%
1.04 × 10-63
 
< 0.1%
1.05 × 10-69
0.1%
1.06 × 10-64
< 0.1%
1.07 × 10-66
< 0.1%
1.08 × 10-64
< 0.1%
1.09 × 10-61
 
< 0.1%
ValueCountFrequency (%)
0.996 1
< 0.1%
0.987 1
< 0.1%
0.985 1
< 0.1%
0.983 1
< 0.1%
0.977 2
< 0.1%
0.976 1
< 0.1%
0.975 1
< 0.1%
0.972 1
< 0.1%
0.968 1
< 0.1%
0.966 1
< 0.1%

liveness
Real number (ℝ)

Distinct1407
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.19578228
Minimum0.0119
Maximum0.992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:14.486429image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0.0119
5-th percentile0.0607
Q10.097275
median0.129
Q30.256
95-th percentile0.514
Maximum0.992
Range0.9801
Interquartile range (IQR)0.158725

Descriptive statistics

Standard deviation0.15925775
Coefficient of variation (CV)0.81344311
Kurtosis5.6447911
Mean0.19578228
Median Absolute Deviation (MAD)0.0476
Skewness2.1782646
Sum2818.4817
Variance0.02536303
MonotonicityNot monotonic
2023-08-29T11:54:14.802234image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11 172
 
1.2%
0.109 166
 
1.2%
0.111 158
 
1.1%
0.112 153
 
1.1%
0.107 150
 
1.0%
0.108 149
 
1.0%
0.104 146
 
1.0%
0.103 140
 
1.0%
0.101 132
 
0.9%
0.105 131
 
0.9%
Other values (1397) 12899
89.6%
ValueCountFrequency (%)
0.0119 1
 
< 0.1%
0.0136 3
< 0.1%
0.0157 1
 
< 0.1%
0.0169 1
 
< 0.1%
0.0208 1
 
< 0.1%
0.0214 1
 
< 0.1%
0.0219 1
 
< 0.1%
0.0233 1
 
< 0.1%
0.0243 1
 
< 0.1%
0.0246 1
 
< 0.1%
ValueCountFrequency (%)
0.992 1
 
< 0.1%
0.989 2
< 0.1%
0.988 2
< 0.1%
0.987 1
 
< 0.1%
0.986 3
< 0.1%
0.985 2
< 0.1%
0.984 2
< 0.1%
0.983 2
< 0.1%
0.982 3
< 0.1%
0.981 1
 
< 0.1%

valence
Real number (ℝ)

Distinct1268
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.48637902
Minimum0.0215
Maximum0.986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:15.113042image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0.0215
5-th percentile0.107
Q10.299
median0.4805
Q30.672
95-th percentile0.891
Maximum0.986
Range0.9645
Interquartile range (IQR)0.373

Descriptive statistics

Standard deviation0.23947618
Coefficient of variation (CV)0.49236537
Kurtosis-0.9124495
Mean0.48637902
Median Absolute Deviation (MAD)0.1865
Skewness0.08868735
Sum7001.9123
Variance0.057348842
MonotonicityNot monotonic
2023-08-29T11:54:15.403862image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.389 38
 
0.3%
0.369 34
 
0.2%
0.352 34
 
0.2%
0.399 34
 
0.2%
0.589 33
 
0.2%
0.412 33
 
0.2%
0.619 32
 
0.2%
0.394 32
 
0.2%
0.512 31
 
0.2%
0.486 31
 
0.2%
Other values (1258) 14064
97.7%
ValueCountFrequency (%)
0.0215 1
< 0.1%
0.0223 1
< 0.1%
0.0259 1
< 0.1%
0.0262 1
< 0.1%
0.0264 1
< 0.1%
0.0284 1
< 0.1%
0.0307 1
< 0.1%
0.0308 2
< 0.1%
0.0314 1
< 0.1%
0.0317 1
< 0.1%
ValueCountFrequency (%)
0.986 1
 
< 0.1%
0.985 1
 
< 0.1%
0.982 1
 
< 0.1%
0.98 2
 
< 0.1%
0.979 2
 
< 0.1%
0.978 2
 
< 0.1%
0.977 3
< 0.1%
0.975 5
< 0.1%
0.974 7
< 0.1%
0.973 5
< 0.1%

tempo
Real number (ℝ)

Distinct11392
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.69537
Minimum30.557
Maximum217.416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:15.722664image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum30.557
5-th percentile79.51875
Q199.799
median120.06
Q3141.98825
95-th percentile175.78
Maximum217.416
Range186.859
Interquartile range (IQR)42.18925

Descriptive statistics

Standard deviation29.53849
Coefficient of variation (CV)0.24074657
Kurtosis-0.4458828
Mean122.69537
Median Absolute Deviation (MAD)21.01
Skewness0.37650698
Sum1766322.6
Variance872.52242
MonotonicityNot monotonic
2023-08-29T11:54:16.092434image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
119.993 11
 
0.1%
120.024 9
 
0.1%
120 8
 
0.1%
110.016 8
 
0.1%
160.004 8
 
0.1%
110.019 7
 
< 0.1%
100.017 6
 
< 0.1%
100.012 6
 
< 0.1%
130.038 6
 
< 0.1%
124.069 6
 
< 0.1%
Other values (11382) 14321
99.5%
ValueCountFrequency (%)
30.557 1
< 0.1%
34.132 1
< 0.1%
42.956 1
< 0.1%
47.387 1
< 0.1%
49.196 1
< 0.1%
49.32 1
< 0.1%
49.689 1
< 0.1%
50.658 1
< 0.1%
50.767 1
< 0.1%
51 1
< 0.1%
ValueCountFrequency (%)
217.416 2
< 0.1%
216.091 1
< 0.1%
216.053 2
< 0.1%
216.02 1
< 0.1%
212.049 1
< 0.1%
210.164 1
< 0.1%
209.84 1
< 0.1%
209.06 1
< 0.1%
208.634 1
< 0.1%
208.589 1
< 0.1%

duration_in min/ms
Real number (ℝ)

Distinct11805
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200094.22
Minimum0.50165
Maximum1477187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:16.420232image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0.50165
5-th percentile3.3772208
Q1165445.75
median208941
Q3252247
95-th percentile353608.25
Maximum1477187
Range1477186.5
Interquartile range (IQR)86801.25

Descriptive statistics

Standard deviation111689.1
Coefficient of variation (CV)0.55818252
Kurtosis8.6973428
Mean200094.22
Median Absolute Deviation (MAD)43339.5
Skewness0.83640698
Sum2.8805564 × 109
Variance1.2474455 × 1010
MonotonicityNot monotonic
2023-08-29T11:54:16.707052image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192000 11
 
0.1%
230000 9
 
0.1%
216000 8
 
0.1%
235000 7
 
< 0.1%
220000 7
 
< 0.1%
170733 7
 
< 0.1%
208000 7
 
< 0.1%
200000 7
 
< 0.1%
240000 7
 
< 0.1%
210000 6
 
< 0.1%
Other values (11795) 14320
99.5%
ValueCountFrequency (%)
0.50165 1
< 0.1%
0.533916667 1
< 0.1%
0.96915 1
< 0.1%
0.979333333 1
< 0.1%
0.991983333 1
< 0.1%
1.027483333 1
< 0.1%
1.130666667 1
< 0.1%
1.197383333 1
< 0.1%
1.270883333 1
< 0.1%
1.365333333 1
< 0.1%
ValueCountFrequency (%)
1477187 1
< 0.1%
1392667 1
< 0.1%
1385907 2
< 0.1%
1284507 1
< 0.1%
1244613 1
< 0.1%
1233667 1
< 0.1%
1095394 1
< 0.1%
1090787 1
< 0.1%
1083755 1
< 0.1%
1041200 1
< 0.1%

time_signature
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size112.6 KiB
4
13149 
3
 
994
5
 
166
1
 
87

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters14396
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row3
5th row4

Common Values

ValueCountFrequency (%)
4 13149
91.3%
3 994
 
6.9%
5 166
 
1.2%
1 87
 
0.6%

Length

2023-08-29T11:54:16.987879image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-29T11:54:17.245719image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
4 13149
91.3%
3 994
 
6.9%
5 166
 
1.2%
1 87
 
0.6%

Most occurring characters

ValueCountFrequency (%)
4 13149
91.3%
3 994
 
6.9%
5 166
 
1.2%
1 87
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14396
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 13149
91.3%
3 994
 
6.9%
5 166
 
1.2%
1 87
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 14396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 13149
91.3%
3 994
 
6.9%
5 166
 
1.2%
1 87
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 13149
91.3%
3 994
 
6.9%
5 166
 
1.2%
1 87
 
0.6%

Class
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6956794
Minimum0
Maximum10
Zeros500
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size112.6 KiB
2023-08-29T11:54:17.424607image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median8
Q310
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2061699
Coefficient of variation (CV)0.47884162
Kurtosis-0.84661279
Mean6.6956794
Median Absolute Deviation (MAD)2
Skewness-0.66656285
Sum96391
Variance10.279526
MonotonicityNot monotonic
2023-08-29T11:54:17.632479image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
10 3959
27.5%
6 2069
14.4%
9 2019
14.0%
8 1483
 
10.3%
5 1157
 
8.0%
1 1098
 
7.6%
2 1018
 
7.1%
0 500
 
3.5%
7 461
 
3.2%
3 322
 
2.2%
ValueCountFrequency (%)
0 500
 
3.5%
1 1098
7.6%
2 1018
7.1%
3 322
 
2.2%
4 310
 
2.2%
5 1157
8.0%
6 2069
14.4%
7 461
 
3.2%
8 1483
10.3%
9 2019
14.0%
ValueCountFrequency (%)
10 3959
27.5%
9 2019
14.0%
8 1483
 
10.3%
7 461
 
3.2%
6 2069
14.4%
5 1157
 
8.0%
4 310
 
2.2%
3 322
 
2.2%
2 1018
 
7.1%
1 1098
 
7.6%

Interactions

2023-08-29T11:54:01.446525image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:19.750476image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:22.921567image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:26.154202image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:28.961612image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:31.779095image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:34.777750image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:37.955580image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:41.154593image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:44.657006image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:48.644184image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:52.033811image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:55.075071image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:58.403691image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:54:01.691367image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:20.053167image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:23.127731image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:26.361075image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:29.177476image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:31.987581image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:35.031593image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:55.769064image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:52.932626image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:55.979935image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:59.264853image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:54:02.823667image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:20.871909image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:46.719376image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:50.856544image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:25.081457image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:28.127264image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:30.936617image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:33.919870image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:37.091313image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:40.140222image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:43.694601image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:47.626814image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:51.140363image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:31.133493image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:53:34.103759image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
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2023-08-29T11:53:58.196821image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
2023-08-29T11:54:01.237649image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

Correlations

2023-08-29T11:54:17.889318image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
IdPopularitydanceabilityenergykeyloudnessspeechinessacousticnessinstrumentalnesslivenessvalencetempoduration_in min/msClassmodetime_signature
Id1.0000.0090.012-0.0130.005-0.012-0.001-0.0000.020-0.003-0.004-0.0020.0170.0020.0000.000
Popularity0.0091.0000.1640.0310.0090.1250.020-0.062-0.168-0.0600.058-0.003-0.0370.1360.0440.057
danceability0.0120.1641.000-0.1780.007-0.0480.0750.204-0.182-0.1150.438-0.165-0.161-0.1340.0790.112
energy-0.0130.031-0.1781.0000.0110.7350.352-0.728-0.0670.1790.1640.2020.2020.2220.0480.129
key0.0050.0090.0070.0111.0000.0020.007-0.002-0.0070.0040.0310.0210.006-0.0030.2570.028
loudness-0.0120.125-0.0480.7350.0021.0000.230-0.560-0.2400.1160.1160.1490.0840.2010.0400.106
speechiness-0.0010.0200.0750.3520.0070.2301.000-0.210-0.0380.1000.0570.121-0.022-0.0490.0650.055
acousticness-0.000-0.0620.204-0.728-0.002-0.560-0.2101.000-0.011-0.1100.007-0.179-0.290-0.2590.0280.119
instrumentalness0.020-0.168-0.182-0.067-0.007-0.240-0.038-0.0111.000-0.032-0.198-0.0110.092-0.0740.0210.062
liveness-0.003-0.060-0.1150.1790.0040.1160.100-0.110-0.0321.000-0.0050.0280.0150.0230.0110.016
valence-0.0040.0580.4380.1640.0310.1160.0570.007-0.198-0.0051.0000.050-0.147-0.0570.0210.093
tempo-0.002-0.003-0.1650.2020.0210.1490.121-0.179-0.0110.0280.0501.0000.0240.0470.0340.057
duration_in min/ms0.017-0.037-0.1610.2020.0060.084-0.022-0.2900.0920.015-0.1470.0241.0000.1820.0870.060
Class0.0020.136-0.1340.222-0.0030.201-0.049-0.259-0.0740.023-0.0570.0470.1821.0000.1430.104
mode0.0000.0440.0790.0480.2570.0400.0650.0280.0210.0110.0210.0340.0870.1431.0000.016
time_signature0.0000.0570.1120.1290.0280.1060.0550.1190.0620.0160.0930.0570.0600.1040.0161.000

Missing values

2023-08-29T11:54:05.156217image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-29T11:54:05.864779image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-29T11:54:06.437422image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

IdArtist NameTrack NamePopularitydanceabilityenergykeyloudnessmodespeechinessacousticnessinstrumentalnesslivenessvalencetempoduration_in min/mstime_signatureClass
01Marina MaximilianNot Afraid37.00.3340.5369.0-6.64900.03810.378000NaN0.10600.2350152.429204947.00000049
12The Black KeysHowlin' for You67.00.7250.74711.0-5.54510.08760.0272000.0468000.10400.3800132.921191956.00000046
23Royal & the Serpentphuck uNaN0.5840.8047.0-6.09410.06190.0009680.6350000.28400.6350159.953161037.000000410
34Detroit Blues BandMissing You12.00.5150.308NaN-14.71110.03120.9070000.0213000.30000.5010172.472298093.00000032
45Coast ContraMy Lady48.00.5650.7776.0-5.09600.24900.183000NaN0.21100.619088.311254145.00000045
56BeckFuckin With My Head (Mountain Dew Rock)38.00.6570.8137.0-7.86110.21600.0083400.0492000.20800.589082.035219587.000000410
67Shadow and LightBlue11.00.6580.4311.0-12.71800.03000.6150000.2920000.09020.5280132.0453.89393350
78Within The RuinsDevil In Me45.00.4410.9947.0-2.93410.23900.0000730.0001470.38200.0478139.931213125.00000048
89Crazy CavanMy Little Sister Gotta Motorbike38.00.4460.8169.0-9.76210.07660.318000NaN0.33900.7180183.696165293.000000410
910Day SulanBailar58.00.8520.5357.0-5.94000.08960.4390000.0000820.24600.4830103.007205056.00000045
IdArtist NameTrack NamePopularitydanceabilityenergykeyloudnessmodespeechinessacousticnessinstrumentalnesslivenessvalencetempoduration_in min/mstime_signatureClass
1438614387JatayuShringara17.00.5280.7834.0-6.50400.04970.3000000.7400000.06580.713114.925325762.00000036
1438714388The Jon Spencer Blues ExplosionBellbottoms56.00.3110.8822.0-3.26010.21500.0089500.2050000.25300.435162.189317987.00000042
1438814389Peledהעולם שלי32.00.7080.6909.0-6.58100.06040.011200NaN0.15000.354162.076225267.00000045
1438914390Hadag Nahashחליפות36.00.8120.6179.0-6.34510.26400.154000NaN0.07600.76183.987262893.00000045
1439014391M83Kim & Jessie45.00.4920.5675.0-6.15910.03270.0001140.5360000.35800.245111.010323373.000000410
1439114392NOISYI Wish I Was A...47.00.6070.9461.0-2.96510.15000.0054800.0003900.27800.653120.011195181.000000410
1439214393BLOODSPOTDeadline Story (feat. Patrick Boos)27.00.4350.9518.0-7.47510.05760.0000050.5500000.09520.203135.034282043.00000048
1439314394Cold YearsToo Far Gone22.00.4150.94111.0-4.30010.05240.0018100.0000040.33700.572167.978176529.000000410
1439414395The Jaded Hearts ClubReach Out I'll Be There37.00.4930.9861.0-2.27910.09170.0009670.0066200.12300.567122.036186307.000000410
1439514396Freddy FenderBefore the Next Teardrop Falls50.00.7990.34510.0-11.52010.02760.7480000.0000240.16900.77690.4172.61456744